Location of curved structure

ABSTRACT

In a method and apparatus for locating in a three dimensional data array an arcuate object having an axial extent, slices of data generally transverse to the axial extent of the object are selected. Rays generally radially of the arcuate object are selected within the slices. Crossing points where the rays cross the boundaries of the arcuate object are located. The position of the arcuate object is determined from the positions of the located points.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 60/682,971, filed May 20, 2005, which is imported hereinby reference in its entirety.

This application is related to the following U.S. patent applicationswhich are filed on even date herewith and which are incorporated hereinby reference:

-   -   Ser. No. 11/XXX,XXX (Attorney Docket No.:        45058-0005-00-US (225687) entitled LOCATION OF ELONGATED OBJECT;    -   Ser. No. 11/XXX,XXX (Attorney Docket No.:        45058-0007-00-US (226421) entitled LOCATION OF FOCAL PLANE; and    -   Ser. No. 11/XXX,XXX (Attorney Docket No.:        45058-0009-00-US (226711) entitled PANORAMIC VIEW GENERATOR.

BACKGROUND

The invention relates to locating a curved object in a three-dimensionalarray of data, and especially, but not exclusively, to locating anunevenly curved structure in a tomographic imaging dataset. Theinvention has particular application to locating the maxilla, themandible, or both in a dataset of part of the head of a human or othermammal.

In certain forms of dental medicine and surgery, a “panoramic” image ofthe jaw is used to examine the jaw, for example, for monitoring ofdental health and condition, diagnosis, and planning of prosthetic andother surgical procedures. The panoramic image of the jaw, like apanoramic photograph, depicts the jaw as if it were imaged onto animaginary approximately cylindrical sheet with the axis of the sheetupright, and the sheet were then unrolled into a flat form. However, thehuman jaw is not a perfect circular arc, so the “cylindrical” shape ofthe imaginary sheet is not exactly circular.

A set of three-dimensional data relating to a property of an object thatvaries over space within the object may be obtained in various ways. Forexample, an x-ray image of a target may be obtained by placing thetarget between a source of x-rays and a detector of the x-rays. In acomputed tomography (CT) system, a series of x-ray images of a targetare taken with the direction from the source to the detector differentlyoriented relative to the target. From these images, a three-dimensionalrepresentation of the density of x-ray absorbing material in the targetmay be reconstructed. Other methods of generating a three-dimensionaldataset are known, including magnetic resonance imaging, or may bedeveloped hereafter.

From the three-dimensional data, a desired section or “slice” may begenerated, including a curved slice. For example, a slice curving alongthe jaw, corresponding to a panoramic view of the jaw may be generated,provided that the position of the jaw within the three-dimensionaldataset is known. It has previously been proposed to display on a visualdisplay unit (VDU) a horizontal section through the mandible or maxilla,and for a human user to identify, for example by controlling a cursor onthe VDU or by using a stylus on a touch-sensitive VDU, enough points onthe mandible or maxilla for the curve of the jaw to be interpolated.However, many dentists and oral surgeons are not skilled computeroperators.

There is therefore a hitherto unfulfilled need for a system by which thearc of the jaw can be accurately identified in a tomographic datasetwithout relying on the skill of a human operator, so that panoramic andsimilar images can be reliably automatically generated.

SUMMARY

According to one embodiment of the invention, there is provided a methodand system for locating in a three dimensional data array an arcuateobject having an axial extent. Slices of data generally transverse tothe axial extent of the object are selected. Rays generally radially ofthe arcuate object are selected within the slices. Crossing points wherethe rays cross the boundaries of the arcuate object are located. Theposition of the arcuate object is determined from the positions of thelocated points.

According to a preferred embodiment of the invention, the data array isa tomographic dataset of a human head or part thereof, and the curvedobject is the upper or lower jaw.

By locating the mandible or maxilla in the three-dimensional tomographicdataset, and exploiting the fact that the jaw is continuous along itslength and has relatively sharp boundaries, the curve of the jaw can beidentified with greater reliability than is attainable by most humanoperators without special skills or great effort.

The invention also provides computer software arranged to generate animage in accordance with the method of the invention, andcomputer-readable media containing such software. The software may bewritten to run on an otherwise conventional computer processingtomographic data.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory and areintended to provide further explanation of the invention as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included to provide a furtherunderstanding of the invention and are incorporated in and constitute apart of this specification, illustrate embodiments of the invention andtogether with the description serve to explain the principles of theinvention.

In the drawings:

FIG. 1 is a schematic view of apparatus for generating a tomographicimage.

FIG. 2 is a flow chart of one embodiment of a method according to theinvention.

FIG. 3 is a schematic plan view of a jaw.

FIG. 4 is a schematic side view of a head, with a curve of probabilitydistribution.

FIG. 5 is a flow chart of another embodiment of a method according tothe invention.

DETAILED DESCRIPTION

Reference will now be made in detail to various embodiments of thepresent invention, examples of which are illustrated in the accompanyingdrawings.

Referring to the drawings, and initially to FIGS. 1 and 2, one form oftomographic apparatus according to an embodiment of the invention,indicated generally by the reference numeral 20, comprises a scanner 22and a computer 24 controlled by a console 26 with a display 40. Thescanner 22 comprises a source of x-rays 28, an x-ray detector 30, and asupport 32 for an object to be imaged. In an embodiment, the scanner 22is arranged to image the head, or part of the head, of a human patient(not shown), especially the jaws and teeth. The support 32 may then be aseat with a rest or restrainer 36 for the head or face (not shown) ofthe patient. The x-ray source 28 and detector 30 are then mounted on arotating carrier 34 so as to circle round the position of the patient'shead, while remaining aligned with one another. In step 102, the x-raydetector 30 then records a stream of x-ray shadowgrams of the patient'shead from different angles. The computer 24 receives the x-ray imagedata from the scanner 22, and in step 104 calculates a 3-dimensionalspatial distribution of x-ray density.

The imaging of the patient's head and calculation of the spatialdistribution may be carried out by methods and apparatus already knownin the art and, in the interests of conciseness, are not furtherdescribed here. Suitable apparatus is available commercially, forexample, the i-CAT Cone Beam 3-D Dental Imaging System from ImagingSciences International of Hatfield, Pa.

In step 106, an initial slice 202 through the tomographic dataset isselected. As shown in FIG. 4, the initial slice 202 is a horizontalslice, relative to the normal standing or sitting position of a humanpatient. For other species, the operator may select an appropriateorientation, either by positioning the patient for scanning, or bymanipulation of the tomographic data. The slice may be selected by ahuman operator on the display 40 of the console 26, or may be selectedautomatically by the computer 26.

In step 108, a reference point 204 is selected. The reference point 204is preferably on, or close to, the centerplane of the head, andapproximately at the center of the dental arch. Because the dental archis not an arc of a circle, and may not be symmetrical from side to side,very precise centering of the reference point 204 is not required, andmay not be meaningfully possible. The same reference point 204 will beused in subsequent processing of other slices. Therefore, the referencepoint 204 may be treated as the intersection of a vertical referenceline with the slice 202, and either the reference line/point 204 or theslice 202 may be selected first, or they may be selected in parallel.For subsequent slices 202, the reference point 204 is automaticallyselected as a point on the reference line through the reference point inthe first slice.

In step 110, a probability count is set to zero.

In step 112, a ray 206 in the slice 202 extending radially away from thecenter point 204 through the jaw 200 is selected.

In step 114, the ray 206 is inspected to identify the points 208, 210where the ray crosses the inner face 212 and the outer face 214 of thejaw 200. These faces 212, 214 are typically recognized as ramps in thedensity profile along the ray, where the density rises rapidly towardsthe jaw 200. The bone of the jaws typically has a markedly higherdensity than the surrounding soft tissue. The crossing points 208, 210may be taken as points where the ramp crosses a selected densitythreshold. If the ramps are not clearly defined, for example, if thesteepness or height of either or both ramp is less than a presetthreshold, the ray 206 may be discarded.

If crossing points 208, 210 are identified, in step 116 the crossingpoints may be subjected to a quality test. For example, the ray may bediscarded if the identified crossing points 208, 210 are notapproximately where the jaw 200 is expected to be, are too closetogether or too far apart, or are out of line with the crossing points208, 210 in neighboring rays.

If the ray passes the quality test, in step 117 the probability count isincreased by one, and the position where the ray 206 crosses the jaw isrecorded. In one embodiment, only the center of the jaw, which may betaken as a point 216 midway between the crossing points 208, 210, isrecorded. In another embodiment, the crossing points 208, 210 arerecorded instead, or in addition. If the ray 206 is discarded either atstep 114 because adequate ramps are not found or at step 116 because thequality test is failed, then step 117 is bypassed.

The process then returns to step 112 to select another ray 206 in thesame slice. A selected number of rays 206 evenly spaced around the arcof the jaw are selected. When it is determined in step 118 that all ofthe rays 206 for the slice 202 have been processed, the probabilitycount for the slice 202 is recorded, and the process returns to step 106to select another slice 202.

The process then repeats for each of a stack of slices 202 over a partof the tomographic dataset where, based on the normal positioning of theheadrest 36 relative to the x-ray source 28 and detector 30, the jaw 200is likely to be present. It is not usually necessary to process everyvoxel slice of the original dataset. Preferably, a reasonable number ofslices, which may be evenly spaced or may be more closely spaced inareas of expected high probability, are processed. The initial slice 202may be the top or bottom slice of the stack of slices, with the processworking systematically down or up the stack. However, that is notnecessary, and the initial slice 202 may be an arbitrary slice.

Various methods may be used to define the upper and lower bounds of thestack of slices 202 used in steps 106 to 120. A bound may be set as theupper and/or lower edge of the field of the original scan of part of thepatient's head. A bound may be set manually using a vertical display ofthe dataset. The upper or lower edge of the mandible, or the lower edgeof the maxilla, may be easily found by detecting the point where highdensity tissue (usually teeth or bone) abruptly disappears. Othersuitable methods may also be used.

When it is determined in step 120 that all of the slices 202 have beenprocessed, in step 122 the recorded probability counts for the differentslices 202 are inspected. As shown by the curve 220 in FIG. 4, theprobability counts typically vary from slice to slice, with the highestprobability counts forming a peak where the jaw is most well defined andthe probability value decreasing above and below the peak.Alternatively, a bimodal distribution with distinct peaks for themandible and maxilla may be found. A high probability count indicatesthat few of the rays 206 were discarded, and that many of the rays haveyielded points 216 that are believed correctly to indicate the positionof the jaw.

In step 124, the slice 202 with the highest probability count isselected, and the center points 216 of the selected slice are selected,if the center points were calculated and recorded in step 117, or arecalculated, if only the crossing points 108, 110 were recorded in step117. If the peak of the probability curve 220 has a “plateau,” wheremore than one neighboring slice has the identical highest probabilitycount, any one of those slices can be chosen arbitrarily. All of thoseslices are likely to lie in a “good” region of the jaw. A contour line222 representing the dental arch is then constructed through the points216. Where a bimodal distribution is found, separate contour lines 222may be constructed for the maxilla and the mandible.

In step 126, a synthesized panoramic slice formed from columns of voxelsalong the contour line 222 is then generated and presented to the user.The columns of voxels may be perpendicular to the plane of the slices202, or may be at an angle. Where separate mandibular and maxillarycontour lines 222 have been constructed, the columns of voxels may beslanted or curved to pass through both contour lines 222, giving ahybrid panoramic view that shows both the maxilla and the mandible. Thesynthesized panoramic slice may be one or more voxels thick. Forexample, the thickness of the panoramic slice may correspond to atypical value for the actual thickness of the mandible or maxillaperpendicular to the panoramic slice plane.

The thickness of the human mandible and maxilla vary, both from personto person and from point to point within the jaw. Consequently, thesynthesized panoramic slice displayed in step 126 may be less thanoptimal because it may include too much or too little of the thicknessof the jaw. If the panoramic slice is too thick, bony structure mayoverlay or “shade” detail in the interior of the mandible or maxilla,such as the alveolar nerve, or blur details of the root of a tooth. Ifthe panoramic slice is too thin, bony outgrowths, protrudingcalcification, or displaced teeth may be missed.

Referring now to FIG. 5, in an alternative embodiment of a processaccording to the invention the crossing points 208, 210 are recorded instep 117. Then, after step 120, the process proceeds to step 302 andcalculates inner and outer envelopes of the jaw 200. The inner envelopemay follow the points 208 from all the accepted rays 206 in all theslices 202. The outer envelope may follow the points 210 from all theaccepted rays 206 in all the slices 202. In step 304, the process thengenerates a panoramic slice containing the entire jawbone, except forprojections too small to be reflected in the array of crossing points208, 210.

Alternatively, if it is desired to view the internal structure of themandible or maxilla, part of the cortical bone may be virtually“machined” away to generate a slice in which less bone is present toobscure the view. In step 306, the process may select, or get from auser, a figure for the amount of machining, for example, a “percentageof erosion.” The panoramic slice is then generated in step 308, omittinga corresponding part of the cortical bone. For example, where thepanoramic slice in step 304 extends from −50% to +50% of the thicknessof the jaw, centered on the contour 222 at 0%, a panoramic slice with30% erosion may extend from −35% to +35%. Other patterns of erosion ormachining may be used, for example, removal of a constant thickness ofbone.

In step 310, the tomographic data generated as described above withreference to steps 102, 104 in FIG. 2 may be subjected to a segmentationprocess known in other fields to discriminate between the targetedmandible or maxilla and other tissues. The segmentation processtypically comprises of defining an initially arbitrary contour throughthe dataset. The contour may be a surface in the three dimensionaldataset or a line in a slice 202. In an iterative process, the contouris then adjusted and assessed by some criterion for its fit to thesurface of the mandible or maxilla. The criterion may test, for example,how much of the contour is in areas of high density gradient. Theiterative process may lock into place parts of the contour that are onlocal maxima of the density gradient, while continuing to adjust otherparts of the contour. Segmentation processes and suitable iterativealgorithms are well known in other fields of image processing, and inthe interests of conciseness the segmentation is not further discussedhere.

Where the segmentation process is carried out using a surface as thecontour, the final result may be equivalent to the envelope generated instep 302, and may be passed directly to steps 304 and 306. Where thesegmentation process is carried out on individual slices 202, the slicecontours may be stacked and an envelope interpolated similarly to step202. Where both an envelope surface from step 302 and a segmentationsurface from step 310 are available, the two surfaces may be compared instep 312 to corroborate the identification of the actual jaw surface.Alternatively, portions of the jaw may be located by the process ofsteps 106 to 120, and portions by segmentation, and combined in step 312to give a full surface. For example, a three dimensional segmentationprocess may be better suited to parts of the head where the bone surfaceis not close to vertical relative to the axis 204.

Also, the segmentation process can identify and distinguish separatebony structures in the same dataset. In FIG. 2, only one good set ofpoints 216 is needed, so if some rays 206 inadvertently detect edges onstructures other than the targeted mandible or maxilla, those rays, andif necessary entire slices 202, can be discarded as aberrant. However inFIG. 5, it is desirable to have as many correctly identified points 208,210 as possible, or as nearly a continuous surface found by segmentationas possible, so using the segmentation method to separate out other bonystructures and reduce the amount of data discarded as ambiguous orunclear can be beneficial. Step 114 may then accept multiple crossingpoints 208, 210, and a later step, for example, step 116, may usesegmentation or other discrimination process to select the crossingpoint 208 or 210 that belongs to the targeted mandible or maxilla.

Various modifications and variations can be made in the presentinvention without departing from the spirit or scope of the invention.For example, the order of the steps may be changed. In FIG. 2, more thanone, or all, of the rays 206 may be processed to identify the crossingpoints 208, 210 before the first rays 206 are subjected to the qualitytest in step 116. In particular, the test for out-of-line points cannotusually be completed until points from neighboring rays 206 areavailable for comparison. Alternatively, or in addition, rays inneighboring slices 202 may be used for comparison.

In a further alternative, in step 124 two or more slices 202 with highprobability counts may be combined. An average of the positions of thecontour lines 222, which may be weighted according to the probabilitycounts of the respective slices 202, may be used, or a consensus curvemay be determined by combining only contour lines 222 that agree withina narrow tolerance.

As described with reference to FIG. 2, steps 106 through 120 repeat foreach of a stack of slices 202 over the height of the jaw 200.Alternatively, the process may start with a slice 202 near the expectedlocation of the probability peak of curve 220. The process may thenproceed both up and down, with the probability count being reviewed aseach slice is completed. Step 120 may then terminate the process in eachdirection when the probability count drops below a threshold, which maybe either absolute or relative to the highest detected count, so thatthe process is confident that the peak is within the part of the stackof slices 202 that has been processed.

Where steps 114 and 116 find only one clear crossing point 208 or 210,step 302 may use that one point, although in step 124, a single crossingpoint 208 or 210 may be unhelpful for constructing the center point 216.

For example, FIG. 1 shows that the computer 24 on which the processes ofFIGS. 2 and 5 is running is connected to the scanner 22. A singlecomputer 24 may both control the scanner 22 and run the processes ofFIGS. 2 and 5. Alternatively, part or all of the process of FIG. 2and/or FIG. 5 may be carried out on a separate computer. The data fromthe scanner 22 may be transferred from computer to computer in aconvenient format, for example the DICOM format, at a convenient stageof the process. The data may, for example, be transferred directly fromcomputer to computer or may, for example, be uploaded to and downloadedfrom a storage server.

For example, in the processes described above, it is assumed that thenumber of rays is equal in all slices, and the rays are uniformlyspaced. The number of rays may vary from slice to slice, provided thatan appropriate allowance is made at steps 122 and 124. The rays may bemore closely spaced at parts of the jaw where a small radius ofcurvature and/or a rapid change in curvature is expected. In the processof FIG. 2, for example, the selected slice may have a few discardedrays, and the ray spacing is desirably sufficiently close that a correctcontour 222 can be interpolated with a desired degree of accuracy acrossat least one missing point 216.

For example, it is not necessary for the reference points 204 of thedifferent slices 202 all to lie on a straight line. However, usingconsistent reference points 204 typically gives more consistent, andthus more comparable results, and may give a more accurate decision instep 124. In step 302, using consistent reference points 204 gives amore consistent relationship between the arrays of crossing points 208and 210 and may make the generation of the envelopes computationallysimpler. In addition, using a vertical line of points 204 is usually thesimplest approach.

Although distinct embodiments have been described, features of differentembodiments may be combined. For example, the contour 222 shown in FIG.3 may be obtained as a middle line between inner and outer contoursobtained by the segmentation process of step 310.

Thus, it is intended that the present invention cover modifications andvariations of this invention provided they come within the scope of theappended claims and their equivalents.

1. A method of locating in a three dimensional data array an arcuateobject having an axial extent, comprising: selecting slices of datagenerally transverse to the axial extent of the object; selecting raysgenerally radially of the arcuate object within the slices; locatingcrossing points where the rays cross the boundaries of the arcuateobject; determining the position of the arcuate object from thepositions of the located points.
 2. A method according to claim 1,further comprising selecting at least one slice having a relatively highproportion of located crossing points, and wherein determining theposition of the arcuate object comprises determining from the positionsof the located points in the at least one slice.
 3. A method accordingto claim 2, further comprising selecting a certain number of rays ineach selected slice, and counting the number of located crossing points.4. A method according to claim 2, further comprising discarding crossingpoints that are inconsistent with crossing points detected inneighboring rays.
 5. A method according to claim 1, wherein locatingcrossing points further comprises detecting a first crossing point wherethe ray enters the arcuate object and a second crossing point where theray leaves the arcuate object, and wherein determining the position ofthe arcuate object comprises determining a midpoint between the firstand second crossing points and determining a contour through themidpoints.
 6. A method according to claim 5, further comprisingselecting a slice of data centered on the contour through the midpoints.7. A method according to claim 1, further comprising generating surfacesthrough detected crossing points on an inside and an outside surface ofthe arcuate object.
 8. A method according to claim 7, further comprisingselecting a slice of data comprising the data occupying a proportion ofthe space between the inner and outer generated surfaces.
 9. A methodaccording to claim 1 of providing an improved image of an anatomicalfeature, wherein the data array comprises tomographic data of at leastpart of a human or animal.
 10. A method according to claim 9, whereinthe data array comprises tomographic data of at least one of a mandibleand a maxilla.
 11. A computer program for locating an arcuate objecthaving an axial extent in a three dimensional data array, comprisinginstructions to cause a computer to: select slices of data generallytransverse to the axial extent of the object; select rays generallyradially of the arcuate object within the slices; locate crossing pointswhere the rays cross the boundaries of the arcuate object; and determinethe position of the arcuate object from the positions of the locatedpoints.
 12. A computer program according to claim 11, further comprisinginstructions to cause the computer to select at least one slice having arelatively high proportion of located crossing points, and to determinethe position of the arcuate object from the positions of the locatedpoints in the at least one slice.
 13. A computer program according toclaim 11, further comprising instructions to cause the computer toselect a certain number of rays in each selected slice, and count thenumber of located crossing points in each selected slice.
 14. A computerprogram according to claim 11, further comprising instructions to causethe computer to discard crossing points that are inconsistent withcrossing points detected in neighboring rays.
 15. A computer programaccording to claim 11, further comprising instructions to cause thecomputer to detect a first crossing point where the ray enters thearcuate object and a second crossing point where the ray leaves thearcuate object, to determine a midpoint between the first and secondcrossing points, and to determine a curve through the midpoints.
 16. Acomputer program according to claim 11, further comprising instructionsto cause the computer to generate surfaces through detected crossingpoints on an inside and an outside surface of the arcuate object.
 17. Acomputer program according to claim 16, further comprising instructionsto cause the computer to select a slice of data comprising the dataoccupying a proportion of the space between the inner and outergenerated surfaces.
 18. A machine-readable medium containing a computerprogram according to claim
 11. 19. Apparatus comprising a computerprogrammed with a program according to claim
 19. 20. Apparatus accordingto claim 19, further comprising a tomographic scanner, and arranged togenerate the three dimensional data array from data generated by thescanner so as to represent an object scanned by the scanner.